Insect sensing systems and methods

ABSTRACT

One example insect sensing system includes a light emitter configured to emit light; a structured light generator positioned to receive the emitted light and configured to generate structured light from the emitted light; a plurality of light sensors arranged in a line, each of the light sensors oriented to receive at least a portion of the structured light and output a sensor signal indicating an amount of light received by the respective light sensor; a processing device configured to: obtain the sensor signals from each of the light sensors, and determine a presence of an insect based a received sensor signal from at least one light sensor, the sensor signal indicating a reduced amount of received light by the at least one light sensor. Another example insect sensing system includes a camera comprising an image sensor and a lens having an aperture of f/2.8 or wider; and a processor configured to obtain an image from the camera and detect an insect in the image.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of co-pending U.S. patent applicationSer. No. 15/787,182, filed Oct. 18, 2017, titled “Insect Sensing Systemsand Methods,” the entirety of which is hereby incorporated herein byreference.

FIELD

The present application generally relates to insect release mechanisms,and more specifically relates to insect sensing systems and methods.

BACKGROUND

All continents except Antarctica suffer from the plague ofmosquito-vectored diseases. Various techniques for the control ofmosquito populations involve the generation of sterile male insects forrelease into the wild for mating with local females. These techniquesrequire systems for releasing the reared insects into the wild.

SUMMARY

Various examples are described for insect sensing systems and methods.One example sensing system includes a light emitter configured to emitlight; a structured light generator positioned to receive the emittedlight and configured to generate structured light having a shape; aplurality of light sensors arranged according to the shape, each of thelight sensors oriented to receive at least a portion of the structuredlight and output a sensor signal indicating an amount of light receivedby the respective light sensor; a processing device configured to:obtain the sensor signals from each of the light sensors, and determinea presence of an insect based a received sensor signal from at least onelight sensor, the sensor signal indicating a reduced amount of receivedlight by the at least one light sensor.

One example method includes emitting light using a light emitter;generating structured light having a shape; receiving at least some ofthe structured light using a plurality of light sensors arrangedaccording to the shape, each of the light sensors oriented to receivestructured light and output a signal indicating an amount of lightreceived by the respective light sensor; obtaining the signals from eachof the light sensors; determining a presence of an insect based on areduced amount of received light based on a received signal from atleast one light sensor and an average amount of received light from oneor more of the light sensors, the reduced amount of received light belowa reference threshold.

Another example sensing system includes a camera comprising an imagesensor and a lens having an aperture of f/2.8 or wider, the camerapositioned to capture an image including an interior portion of aninsect release tube, the camera oriented at an oblique angle to alongitudinal axis of the insect release tube, and a depth of focus ofthe camera is located within an interior volume of the insect releasetube; and a processor in communication with a non-transitorycomputer-readable medium and configured to execute processor-executablecode stored in the non-transitory computer-readable medium to: obtain animage from the camera; and detect an insect in the image.

Another example method includes obtaining an image from a cameracomprising an image sensor and a lens having an aperture of f/2.8 orwider; and detecting an insect in the image using an edge detectiontechnique; wherein: the camera is positioned to capture images of aninterior volume of an insect release tube, the camera is oriented suchthat a focal axis of the camera is oriented at an oblique angle to alongitudinal axis of the release tube, and a depth of focus of thecamera is located within the interior volume of the insect release tube

These illustrative examples are mentioned not to limit or define thescope of this disclosure, but rather to provide examples to aidunderstanding thereof. Illustrative examples are discussed in theDetailed Description, which provides further description. Advantagesoffered by various examples may be further understood by examining thisspecification.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated into and constitute apart of this specification, illustrate one or more certain examples and,together with the description of the example, serve to explain theprinciples and implementations of the certain examples.

FIG. 1 shows an example system for releasing insects from a container;

FIGS. 2-8 show example insect sensing systems;

FIG. 9 shows a simulated image captured by an example insect sensingsystem;

FIGS. 10-12 show example insect sensing methods; and

FIG. 13 shows an example computing device for insect sensing systems andmethods.

DETAILED DESCRIPTION

Examples are described herein in the context of insect sensing systemsand methods. Those of ordinary skill in the art will realize that thefollowing description is illustrative only and is not intended to be inany way limiting. Reference will now be made in detail toimplementations of examples as illustrated in the accompanying drawings.The same reference indicators will be used throughout the drawings andthe following description to refer to the same or like items.

In the interest of clarity, not all of the routine features of theexamples described herein are shown and described. It will, of course,be appreciated that in the development of any such actualimplementation, numerous implementation-specific decisions must be madein order to achieve the developer's specific goals, such as compliancewith application- and business-related constraints, and that thesespecific goals will vary from one implementation to another and from onedeveloper to another.

To help eliminate insect-borne diseases, sterile male insects, such asmosquitoes, may be released into an environment, where they mate withfemale insects, but will not generate any offspring. Thus, the insectpopulation is reduced over time. To help effectively control an insectpopulation in such a way, it can be important to know the number ofinsects being released into a particular area. However, thousands ofinsects may be released in a relatively short time, e.g., a few minutes,while a release vehicle travels through an area, and so it can bedifficult to accurately detect the actual number of insects beingreleased at any particular time at any particular location.

FIG. 1 shows an example insect release system 100, which includes aninsect container 110 having a population of insects 112 a-n. The insectcontainer 110 is connected to the proximate end of a release tube 120,through which insects may travel and escape from the insect containerand into the environment via the release opening 122 at the distal endof the release tube. Such a release system 100 may also include a fan orblower to encourage the insects to exit the container 110 and therelease tube 120, or to increase the flight speed of the insects.

Referring now to FIG. 2, to count the insects as they are released, asensing system 210 according to this disclosure may be used to countinsects as they travel through the release tube 120. The sensing system210 sends signals to the computing device 212, which may then countinsects based on the received signals. Some examples of suitable insectsensing systems are described in detail below with respect to FIGS. 3-9.Further, while the insect sensing system 210 is located at a particularposition on the release tube 120, it should be appreciated that aninsect sensing system 210 according to this disclosure may be positionedat any suitable location along the length of the release tube 120.

FIG. 3 illustrates an insect release system 100 that includes an exampleinsect sensing system 300 that includes a light source 310, a structuredlight generator 312, a number of light sensors 320 a-k (“k” representsany integer greater than 1), and a computing device 330 that controlsthe light source 310 and receives sensor signals from the light sensors.In this example, the light source 310 emits light, which strikes thestructured light generator 312. The structured light generator 312receives the incoming emitted light and generates structured light 314that is projected across the interior volume of the release tube 120towards the light sensors 320 a-k. The light sensors 320 a-k areoriented to align with the structured light 314 and output signals tothe computing device 330 based on the amount of light received at eachrespective light sensor.

Structured light according to this disclosure refers to light rays thatare oriented to generate a specific shape. For example, output from alight source may be structured to generate a line, a circle, arectangle, etc. Any suitable structured light generator may be employed,and may include the use of one or more lenses, including laser linegenerator lenses, convex or concave lenses; one or more mirrors; one ormore diffraction elements, such as prisms; one or more diffuserelements; etc. In one example, a structured light generator may includea plate or other flat piece of material having a hole formed at alocation corresponding to a light source, such as an LED, to allow onlya small portion of the light from the light source to pass through thehole. In some examples, multiple light sources and corresponding holesmay be employed. Further, by adjusting the position of the holes withrespect to the light sources, an angle of light passing through the holemay be accurately adjusted and controlled. In some examples, generatingstructured light may also involve techniques such as collimation togenerate parallel rays of light. Collimation may be performed using acollimation structure, such as a Fresnel lens, a convex lens, a fiberoptic coupler, etc. It should be appreciated, however, the structuringlight may or may not involve collimation.

In this example, the light source 310 is a laser-light source, but maybe any suitable light source. In some examples, it may be advantageousto employ substantially monochromatic light, and so one or more lightfilters may be employed to reduce the number of wavelengths of lightprovided to the structured light generator 312, or projected from thestructured light generator 312 across the interior volume of the releasetube 120. Employing substantially monochromatic light may allow thecomputing device 330 to more easily filter ambient light signals fromthe sensor signals received from the light sensors 320 a-k.

In this example, each light sensor 320 a-k is a discrete phototransistorthat is separated by approximately 1 mm from each adjacentphototransistor; however, any suitable spacing may be employed. Spacingmay be selected based on the size of the insects to be detected in aparticular example. For example, to detect mosquitoes, light sensors maybe separated by approximately 1 mm or less to provide sufficientresolution such that a mosquito is unlikely to pass through thestructured light 314 at a location with no corresponding light sensor.In some examples, however, light sensors 320 a-k may be spaced atintervals greater than 1 mm. For example, larger insects, such as flies,may allow for greater spacing between light sensors, e.g., 3 mm or more.Spacing of light sensors may therefore be based on the average orexpected size of insects that will traverse the release tube. And whilein this example, the light sensors 320 a-k are discrete electroniccomponents, such as a phototransistor, a photodiode, or a photoresistor,in some examples, suitable light sensors may be embedded on a monolithiccomponent, e.g., an image sensor such as charge-coupled device (“CCD”),CMOS image sensor, etc. In this example, the light sensors 320 a-koutput a current in proportion to an amount of light received; however,in some examples, the light sensors 320 a-k may output a signalindicating a voltage, resistance, etc. indicating an instantaneousamount of light received by the light sensor. In some examples, however,light sensors may output an average amount of light received over aperiod of time, or may output a digital value indicating an amount oflight received.

The structured light 314 in this example is projected across theinterior volume of the release tube 120 at an angle perpendicular to thelength of the release tube 120, and across the entire cross-section ofthe release tube. However, other examples may be projected at an obliqueangle with respect to the length of the release tube 120. Thepositioning of the light sensors 320 a-k with respect to the lightsource 310 is based on the angle of the structured light projected bythe structured light generator 312. Thus, the light sensors 320 a-k areplaced to receive the structured light 314. However, because ambientlight may also be detected by the light sensors, the light sensors 320a-k may be placed distant from the release opening 122. In this example,the release tube 120 is approximately three feet long, and the lightsensors 320 a-k are positioned approximately 18 inches from the releaseopening 122. It should be appreciated that these dimensions are onlyexamples, and any suitable length of release tube 120 may be employed,and the light sensors 320 a-k may be placed at any position along thelength of the release tube 120 according to different design goals orrequirements.

The computing device 330 is any suitable computing device, such as thecomputing device 1300 described with respect to FIG. 13 below. It is incommunication with both the light sensors 320 a-k and the light source310 (communication link not shown), and is configured to transmit asignal to activate or deactivate the light source 310. In some examples,however, the computing device 330 is not in communication with the lightsource 310, which instead may be directly connected to a power source.In addition, the computing device 330 is configured to receive sensorsignals from the light sensors 320 a-k and detect insects based on thereceived sensor signals. In this example, each individual light sensortransmits its own sensor signals; however, in some examples, the sensorsignal may include information from multiple light sensors, e.g., in thecase of an image sensor.

In operation, insects 112 a-n (where “n” represents any integer greaterthan 1) are allowed to travel from the insect container 110 through therelease tube 120, through the structured light 314, and out the releaseopening 122. In this example, the computing device 330 receives sensorsignals from the light sensors 320 a-k and determines an approximateaverage sensor value for each light sensor 320 a-k to determine abaseline value for each detector when no insect is present. Thecomputing device 330 samples the received sensor signals at a rate ofapproximately 10,000 samples per second and compares each sample againstthe determined average sensor value. When a sensor signal deviates fromthe average sensor value for a respective light sensor by a thresholdamount, the computing device 330 registers an insect and increments aninsect counter and ignores subsequent sensor signals from thatparticular light sensor, until the sensor signal returns to the averagesensor value (or within a threshold amount of the average sensor value).The computing device 330 then determines that the insect has entirelypassed through the structured light 314 and begins looking for the nextinsect. It should be appreciated that a single insect may interfere withlight received by multiple light sensors. Therefore, in some examples,the computing device 330 may determine that multiple adjacent lightsensors all indicate a reduction in detected light and determine each ofthe detectors is detecting the same insect. However, if the spacing ofthe light sensors 320 a-k is sufficiently high, the computing device 330may treat every individual reduction in detected light at a differentsensor as a distinct insect.

While in the example described above, the computing device 330 compareseach sample against a determined average sensor value, in some examples,such a comparison may be performed in circuitry outside of the computingdevice 330. For example, comparators may be employed to compare receivedsensor values against threshold values, such as average sensor values.The output of the comparators may then be provided to the computingdevice 330, either directly or via one or more intermediate components,such as amplifiers, inverters, etc.

Referring now to FIG. 4, FIG. 4 shows an example insect sensing system400. The insect sensing system 400 includes a light source 410, astructured light generator 412, a Fresnel lens 413, and multiple lightsensors 420 a-k. In this example, the light source 410 is a solid statelaser. As can be seen in the figure, light emitted from the light source410 is received by the structured light generator 412, which generatesstructured light that is then passed through the Fresnel lens 413 tocollimate the structured light 414 that is ultimately projected acrossthe interior volume of the release tube 430. The structured light 414traverses the interior volume of the release tube 430 and arrives at thelight sensors 420 a-k, which provide sensor signals to a computingdevice (not shown). While the example insect sensing system 400 shown inFIG. 4 operates by emitting structured light in one direction, otherexamples may employ structured light emitted in multiple directions.Further, while this example employs a Fresnel lens 413, in someexamples, other types of lenses may be employed. In some examples, noadditional lens may be used and the structured light generator 412directly emits the structured light 414.

The example insect sensing system 500 shown in FIG. 5 employs two lightemitters 510 a-b, each emitting onto a respective structured lightgenerator 512 a-b and through a respective Fresnel lens 513 a-b. Thestructured light generators 512 a-b and Fresnel lenses 513 a-b areoriented such that the structured light emitted by one structured lightgenerator/Fresnel lens combination is emitted in a direction orthogonalto structured light emitted by the other structured lightgenerator/Fresnel lens combination. Light sensors 520 a-k, 522 a-m (“m”refers to any integer greater than 1) are positioned on the oppositeside of the release tube 730 from a respective structured lightgenerator 512 a-b. Such an arrangement may enable higher resolutionsensing of insects passing through the release tube 530, or may providemore robust detection of multiple insects that pass through the insectsensing system 500 substantially simultaneously. Further, as discussedabove with respect to FIG. 4, while this example employs Fresnel lenses513 a-b in addition to the structured light generators 512 a-b, in someexamples, other types of lenses may be employed. In some examples, noadditional lens may be used and the structured light generators 512 a-bdirectly emit the structured light 514.

While this example shows two light sources 510 a-b oriented to projectedstructured light 514 orthogonal to each other, other numbers of lightsource/structured light generator/detector arrangements may be employedin some examples. For example, three light source/structured lightgenerator/detector arrangements may be positioned to detect insectswithin a release tube such that each arrangement is positioned 120degrees offset from each other. However, in such an example, light fromone source may strike a light sensor associated with a different lightsource. Thus, it may be desirable to provide spacing between sets oflight sensors, or to employ different colors or wavelengths of lightemitters to mitigate such effects.

Further, while the example insect sensing system 500 shown in FIG. 5projects structured light 514 from two different sources 510 a-b in thesame plane, in some examples, the light source/structured lightgenerator/detector arrangements may be offset from one another such thatan insect may first traverse structured light from one such arrangementand, after travelling further down the release tube 530, traversestructured light from another light source/structured lightgenerator/detector arrangement. Such an arrangement may allow thecomputing device to compare a number of insects detected by onearrangement and by the other arrangement to provide more accurate insectcounts. For example, if two insects (or a clump of several insects)traverse one sheet of structured light substantially simultaneously, butseparate from each other prior to traversing the second sheet ofstructured light, the computing device may be able to distinguish theindividual insects, rather than an apparently larger insect.

Referring now to FIG. 6, FIG. 6 shows an example insect sensing system600 that employs a lens as a structured light generator 612. As with theexample shown in FIG. 4, this example insect sensing system 600 onlyprojects structured light 614 in one direction across the volume of therelease tube 600. The light source 610 in this example is an LED with adiffusion filter. The structured light 614 is then detected by the lightsensors 620 a-k, which provide sensor signals to a computing device (notshown) to detect one or more insects traversing the release tube 630.

FIG. 7 shows an example insect sensing system 700 similar to the examplesystem 500 shown in FIG. 5. The example system 700 includes two lightsources 710 a-b with corresponding lenses configured as structured lightgenerators 712 a-b and oriented to project light across the interiorvolume of the release tube 730 orthogonal to each other. The lightsensors 720 a-k, 722 a-m detect the structured light 714 from theirrespective light source 710 a-b and provide sensor signals to acomputing device (not shown) indicative of the amount of light detectedby the respective light sensor.

While in this example the two structured light generators 712 a-b areboth lenses, in some examples, multiple different types of structuredlight generators 712 a-b may be employed in the same insect sensingsystem.

Referring now to FIG. 8, FIG. 8 shows an example insect sensing system800. In this example, the system 800 includes a camera 820 positioned tocapture an image of the interior volume of a release tube 120 through atransparent cover 810. As can be seen in FIG. 8, the camera 820 isoriented along a focal axis 826 oblique to the longitudinal axis of therelease tube 120, but in the same plane as the release tube'slongitudinal axis. The system 800 captures successive images of theinterior volume of the release tube 120 within the field of view 822 andcounts the number of insects within the images to determine the numberof insects that have traversed the release tube 120.

To allow the insect sensing system 800 to accurately count the insects,in this example, the camera 820 has a lens aperture of f/2.8, but insome examples has a lens aperture of f/2.0 or wider. In addition, thecamera 820 is configured to have a focal length of approximately 1.5 to2 meters; however, any suitable focal length may be selected based onthe position and orientation of the camera 820 with respect to therelease tube 120. In this example, the camera 820 captures images at aresolution of 1280×720 pixels, but in some examples, lower or higherresolution images may be employed.

The camera is configured to have a shallow depth of focus 824 to allowit to capture images of insects 840 a-c within the release tube 120, butonly to capture insects in focus within a shallow volume within therelease tube 120. The camera 820 may then capture successive images ofthe release tube's interior volume, and the captured images may then beanalyzed by the computing device 830 to identify and count in-focusinsects, while ignoring out-of-focus insects. Such a configuration mayallow the sensing system 830 to identify insects as they move throughthe release tube 120 towards the release opening 122. However, becausethe camera 820 has a shallow depth of focus, each insect traversing therelease tube 120 will only be in focus for a short period of time. Thus,as the camera 820 captures successive images, any individual insect mayonly be in focus for one or two frames. Thus, the system 800 canaccurately count the number of insects traversing the release tube 120over time.

For example, as insects 840 a-c fly through the release tube 120 towardthe release opening 122, insect 840 b enters the depth-of-focus volumewhere the camera 820 captures an image with the insect 840 b in focus,while insects 840 a and 840 c will appear out of focus. Referring toFIG. 9, FIG. 9 shows a simulated example captured image 900 of insects840 a-c. As can be seen, insects 840 a and 840 c appear out of focus,while insect 840 b is in focus. The computing device 830 may identifythe in-focus insect 840 b using, for example, an edge detectiontechnique. The edge detection technique can be configured to detectedges that are relatively sharp, indicating an in-focus object, andignore softer or blurred edges associated with an out-of-focus object.

In one example, the computing device 830 performs edge detection foreach pixel in each image using a pixel window centered on the respectivepixel. This process generates an edge gradient map for the image, whichcan then be analyzed to identify edge gradients above a referencethreshold. If an edge gradient is sufficiently high for a thresholdnumber of adjacent pixels, the computing device 830 may determine anobject, e.g., an insect, has been identified, and increment a counter.In some examples, rather than edge detection techniques, the computingsystem 830 may employ contour recognition techniques or objectrecognition techniques, such as a machine learning technique, torecognize insects within captured images. In one example, a machinelearning technique can be trained to recognize in-focus insects and toignore out-of-focus insects, and when one or more in-focus insects arerecognized within an image, the computing device 830 increments acounter based on the number of recognized in-focus insects.

To capture sufficient images of insects as they traverse the releasetube 120 to provide an accurate insect count, the camera 820 capturesimages at a rate of approximately 60 hertz (“Hz”) in this example. Tohelp ensure that an insect is in-focus for at least one image, a lensmay be selected that provides a depth of field of the average length ofthe subject insects, e.g., 8-10 mm for a mosquito, and, based on anexpected flight speed, a frame rate may be selected where at least oneimage of every insect traversing the release tube 120 is statisticallyprobable. For example, if a depth of field of 20 mm is desired, e.g.,twice the average length of a mosquito, and an expected maximum flightspeed of 2 meters per second (“m/s”) is employed, a frame rate ofapproximately 100 Hz is should capture at least one in-focus image ofevery insect traversing the release tube. If a slightly largerdepth-of-field 824 is employed, e.g., 30 mm, a lower frame rate may beemployed, e.g., 66.67 Hz, which may reduce the computational burden onthe computing device 830 as fewer images are captured, and more timeelapses between each new image. However, a higher frame rate, such as240 Hz, may allow a shallow depth of focus, e.g., 20-30 mm, andaccommodate a faster insect movement speed. It should be appreciated,however, that any suitable frame rate may be employed according todifferent examples.

In some examples, the camera 820 may capture multiple images of the sameinsect, e.g., the insect is moving slowly, the frame rate is selected tocapture multiple in-focus images of insects within a depth of field,etc. The computing device 830, in some examples, may attempt to ensurethat an insect is not double (or triple, etc.) counted. In one example,the computing device 830 employs an optical flow technique to identifymovement of an insect through successive captured images. Using such atechnique, the computing device 830 may identify an insect in two ormore successive images as being the same insect, thereby onlyincrementing a counter by one rather than once for each image in whichthe insect was detected. Such a technique may help ensure a moreaccurate count of insects traversing the release tube 120.

Referring now to FIG. 10, FIG. 10 shows an example insect sensing method1000. The method 1000 will be described with respect to the insectsensing system 300 shown in FIG. 3, however, it should be appreciatedthat any suitable sensing system according to this disclosure may beemployed, including any of the systems 400-700 shown in FIGS. 4-7.

At block 1010, the sensing system 300 emits light using the light source310. In this example, the light source 310 is a laser light source, butin some examples, it may be any suitable light source, including an LED,incandescent light source, a fluorescent light source, etc.

At block 1020, the sensing system 300 generates structured light fromthe emitted light using a structured light generator. In this example,the sensing system 300 also employs a Fresnel lens or a convex lens tocollimate the structured light; however, any suitable structured lightgenerator may be employed, with or without a light collimator.

At block 1030, the sensing system 300 receives at least some of thestructured light using multiple light sensors 320 a-k. In this example,the light sensors 320 a-k are one or more of a photodiode, aphototransistor, or a photoresistor; however, any suitable light sensormay be employed, including a CCD or CMOS image sensor.

At block 1040, the computing device 330 obtains one or more sensorsignals from each of the light sensors 320 a-k. In this example, eachsensor signal indicates an amount of light received by the respectivelight sensor; however, in some examples each sensor signal may indicatean average amount of light received by the respective light sensor overa period of time. In this example, the sensor signal is a voltageproportional to the amount of light received by the respective sensor;however, in some examples, the signal may be a current or a digitalvalue (e.g., a pixel value) indicating an amount of light received. Insome examples, a sensor signal may be a binary value, e.g., 0 or 1,indicating whether a threshold amount of light was received by therespective light sensor. If the threshold amount of light was notreceived by a light sensor, e.g., due to an insect blocking some of thestructured light, the sensor may output a binary 0, while another lightsensor that did receive at least the threshold amount of light, thelight sensor may output a binary 1.

At block 1050, the sensing system 300 determines the presence of aninsect based on a received sensor signal from at least one light sensorwhere the signal indicates a reduced amount of received light. In thisexample, the computing device 330 receives sensor signals from the lightsensors 320 a-k over time and, for each of the light sensors 320 a-k, itdetermines an average amount of light received. Thus, if an insectobstructs (or partially obstructs) a portion of the structured light,one or more light sensors 320 a-k may output a sensor signal indicatingan amount of received light that is less than the average amount ofreceived light for the respective light sensor.

Because, in some examples, each light sensor 320 a-k may experiencevariations in the amount of light received due to ambient light, noise,dust particles, etc., in this example, the computing device 330 maycompare the amount of received light to the average amount of receivedlight for the respective light sensor. If the computing device 330determines that the difference between the two amounts is greater than athreshold, the computing device 330 determines that an insect has beendetected as it passes through the structured light 314. However, if thedifference between the two amounts is less than the threshold, thecomputing device 330 determines that no insect is present. In someexamples, if the difference between the two amounts is less than thethreshold, the computing device 330 may update the average amount ofreceived light for the respective light sensor based on the receivedsensor signal.

In this example, the computing device 330 employs a threshold of 50% ofthe average amount of received light. Thus, if a light sensor 320 a-koutputs an average sensor signal of 5 Volts (“V”), the computing device330 will detect the presence of an insect if the light sensor outputs asensor signal of 2.5 V or less. It should be appreciated that thisthreshold is merely an example, and in some examples, other thresholdsmay be employed.

In some examples, however, rather than maintaining an average amount ofreceived light for each light sensor 320 a-k, the computing device 330may maintain an average amount of light received by all sensors. Thus,received sensor signals from the light sensors 320 a-k may each becompared to this average amount of light received by all sensors.Further, rather than using average sensor values, the computing device330 may instead employ a fixed threshold sensor signal value, e.g., 3.5V, below which an insect is detected and above which no insect isdetected, irrespective of an average value.

While in the example described above, the computing device 330 compareseach sample against a determined average sensor value, in some examples,such a comparison may be performed in circuitry outside of the computingdevice 330. For example, and as described above with respect to FIG. 3,a comparator may be employed to compare a received sensor value againsta threshold value, such as an average sensor value. The output of thecomparator may then be provided to the computing device 330, eitherdirectly or via one or more intermediate components, such as anamplifier, inverter, etc.

It should be appreciated that in some examples, an insect may obstructlight received by multiple light sensors 320 a-k. For example, the lightsensors 320 a-k may be spaced 1 mm apart, while a mosquito traversingthe release tube may have a width of 3-4 mm. Thus, the mosquito mayobstruct structured light received at several light sensors. If thecomputing device 330 detects multiple adjacent light sensors 320 a-keach received an amount of light indicative of an insect being present,the computing device 330 may determine that each of the sensor signalsrelates to the same insect, and thus, the computing device 330 maydetermine the presence of a single insect, despite multiple lightsensors indicating a reduced amount of received light. For example, thecomputing device 330 may be provided with information regarding lightsensor spacing, average or maximum dimensions of the type(s) of insectsthat will be traversing the release tube, or with a parameter indicatinga maximum number of adjacent light sensors that may indicate a signalinsect. Thus, in some examples, if three adjacent light sensors providesensor signals indicating a reduced amount of received light, thecomputing device 330 may determine the presence of one insect. But iffive adjacent light sensors provide sensor signals indicating a reducedamount of received light, the computing device 330 may determine thepresence of two insects.

Further, as discussed above, such as with respect to FIG. 5, structuredlight 314 may be projected in multiple different directions across theinterior volume of the release tube 120. In examples where the differentsources of structured light 512 a-b are co-planar, one or more lightsensors from one set of light sensors 520 a-k may indicate a reducedamount of received light. Similarly, light sensors from the second setof light sensors 522 a-m may also indicate a reduced amount of receivedlight. The computing device 330 may then determine, for each set ofsensors 520 a-k and 522 a-m a number of detected insects. The computingdevice 330 may then determine a total number of detected insects basedon these two different counts of insects. For example, a single insecttraversing the release tube 120 may obstruct light landing on two lightsensors from the first set of light sensors 520 a-k and three lightsensors from the second set of light sensors 522 a-m. Thus, thecomputing device 330 determines that each set of light sensors 520 a-k,522 a-m determined the presence of one insect. Because the structuredlight 314 is coplanar, the total number of detected insects is one.

However, in some examples insects may traverse the release tube 120, andthus the structured light 314, in close proximity to each other.Referring to FIG. 11, two insects 1150 a-b are traversing the structuredlight 1114 of an example insect sensing system 1100. As can be seen inFIG. 11, two sets of light sensors 1120 a-k and 1122 a-m receivestructured light 1114 and, if nothing is obstructing the structuredlight received by a light sensor, it outputs substantially the averageamount of received light 1124 a-b, which may differ for the two sets oflight sensors 1120 a-k, 1122 a-m. However, the insects 1150 a-b areobstructing light received by five light sensors in the first set oflight sensors 1120 a-k and three light sensors in the second set oflight sensors 1122 a-m. Thus, in this example, the computing device 330determines that the first set of light sensors 1120 a-k indicates thepresence of two insects, while the second set of light sensors 1122 a-mindicates the presence of one insect. Thus, to determine the number ofinsects present, the computing device 330 selects the larger of the twovalues and thus determines that two insects are present.

In some examples, the computing device 330 may receive sensor signals ata high rate such that multiple successive sensor signals indicate thesame insect. Thus, in some examples, the computing device 330 maydetermine that if a light sensor outputs sensor signals indicating areduced amount of light for several successive samples, the computingdevice 330 may determine that the successive samples relate to the sameinsect and not determine the presence of a new insect. The number ofsuccessive samples for which a single insect is detected may beestablished based on an expected flight speed of an insect and a samplerate of the sensor signals. Thus, as the sample rate increases, thenumber of successive samples where a single insect may be expected toobstruct structured light may increase. However, as the expected flightspeed increases, the number of successive samples where a single insectmay be expected to obstruct structured light may decrease. Thus, thecombination of the two factors can provide an expected, or maximum,number of successive samples that may relate to the same insect.

At block 1060, the computing device 330 counts the detected insects. Inthis example, the computing device 330 maintains a counter value and,for each insect detected at block 1050, it increments the counter value.

After completing block 1060, the method 1000 returns to block 1040 whereadditional sensor signals are received from the light sensors 520 a-k,522 a-m.

The foregoing examples have described insect sensing systems and methodsthat employ structured light. Other examples of insect sensing systemsand methods may employ different techniques. The following examplesrelate to insect sensing systems and methods that capture images of theinterior volume of a release tube to sense insects as they traverse therelease tube.

Referring now to FIG. 12, FIG. 12 shows an example insect sensing method1200. The method 1200 will be described with respect to the insectsensing system 800 shown in FIG. 8, however, it should be appreciatedthat any suitable sensing system according to this disclosure may beemployed.

At block 1210, the image sensing system 800 obtains an image from thecamera 820. In this example, the camera 820 has an image sensor and alens having an aperture of f/2.8, though in some examples, a camera mayhave a wider lens aperture. In addition, the camera 820 is positionedand oriented generally as described above with respect to FIG. 8, and isconfigured to capture images of the interior volume of the release tube120. In this example, the computing device 830 obtains captured imagesfrom the camera 820 at a predetermined rate, such as between 60 Hz and240 Hz. In some examples, a predetermined rate may be selected such thatthe image sensing system 800 will likely capture multiple in-focusimages of the same insect. Such a predetermined rate may be determinedbased on the depth of focus and the average flight speed of the insectsof the insect population to be released. For example, if the depth offocus is 30 mm and the average insect flight speed is 5 meters persecond, a predetermined sample rate of at 333 Hz would be sufficient toensure at least two images of an insect while it is in focus. In thiscase, sample rate=0.5*focal length (mm)/flight speed (mm/s) to ensure atleast two images are captured. For a larger number of images, n, thesample rate may be computed as

$\frac{n*{flight}\mspace{14mu} {speed}\mspace{11mu} \left( \frac{mm}{s} \right)}{{focal}\mspace{14mu} {length}\mspace{11mu} ({mm})}$

However, sample rates may be determined according to any suitableformula.

At block 1220, the computing device 330 detects one or more insects inthe image. In this example, the computing device 830 detects one or moreinsects in the image using an edge detection technique. Specifically,the computing device 830 searches the image for sufficientlywell-defined edges to identify one or more insects. To do so in thisexample, the computing device 830 performs edge detection for each pixelin each image using a pixel window centered on the respective pixel.This process generates an edge gradient map for the image, which canthen be analyzed to identify edge gradients above a reference threshold.If an edge gradient is sufficiently high for a threshold number ofadjacent pixels, the computing device 830 may determine an insect hasbeen identified. And while this example generates an edge gradient map,in other examples other suitable edge detection techniques may beemployed.

In some examples, other techniques may be employed to detect one or moreinsects, such as trained machine learning techniques, object detectiontechniques, contour recognition techniques, etc. Images obtained by thecomputing device 830 may be provided to one or more such techniques toidentify one or more insects within the images.

At block 1230, the computing device 830 counts the insects detected inthe obtained image and increments a total insect count. In this example,the computing device increments a total insect count by the number ofinsects detected in each image. However, in some examples, the computingdevice 830 may determine that one or more insects appear in multipleimages and not increment the total insect count. For example, thecomputing device 830 may perform one or more optical flow techniques ontwo or more successive images to determine whether any insects detectedin one image were also detected in other images. For example, an imagethat appears in a first image at one position may also appear in asecond image in a different location; however, based on the position,orientation, etc. of the insect in one image, an optical flow techniquemay determine that an insect in another image is the same insect. Thus,the computing device 830 may only increment a total image count once perinsect, even if the detected insect appears in multiple images.

The method 1200 may then return to block 1210 where another image isobtained from the camera 820.

Referring now to FIG. 13, FIG. 13 shows an example computing device 1300suitable for use with one or more insect sensing systems and methodsaccording to this disclosure. The example computing device 1300 includesa processor 1310 which is in communication with the memory 1320 andother components of the computing device 1300 using one or morecommunications buses 1302. The processor 1310 is configured to executeprocessor-executable instructions stored in the memory 1320 to performinsect sensing according to different examples, such as part or all ofthe example methods 1000, 1200 described above with respect to FIGS. 10and 12. The computing device, in this example, also includes one or moreuser input devices 1370, such as a keyboard, mouse, touchscreen,microphone, etc., to accept user input. The computing device 1300 alsoincludes a 1360 display to provide visual output to a user.

The computing device also 1300 includes a wireless transceiver 1330 andcorresponding antenna 1332 to allow the computing device 1300 tocommunicate wirelessly using any suitable wireless communicationprotocol, including WiFi, Bluetooth (“BT”), cellular, etc. techniques.The computing device 1300 also includes a communications interface 1340that enables communications with external devices, such as a camera(e.g., the camera 820 shown in FIG. 8), one or more light emitters(e.g., the light emitters shown in FIGS. 3-7), or one or more lightsensors (e.g., the light sensors shown in FIGS. 3-7). In some examples,the communications interface 1340 may enable communications using one ormore networks, including a local area network (“LAN”); wide area network(“WAN”), such as the Internet; metropolitan area network (“MAN”);point-to-point or peer-to-peer connection; etc. Communication with otherdevices may be accomplished using any suitable networking protocol. Forexample, one suitable networking protocol may include the InternetProtocol (“IP”), Transmission Control Protocol (“TCP”), User DatagramProtocol (“UDP”), or combinations thereof, such as TCP/IP or UDP/IP.

In this example, the computing device 1300 also includes a camera 1350,which may be employed as a camera for insect sensing, such as describedabove with respect to FIG. 8. Thus, in some examples, the camera 820 andthe computing device 830 of FIG. 8 may be incorporated into the samedevice, while in other examples, they may be discrete devices thatcommunicate, e.g., using the communications interface 1340.

While some examples of methods and systems herein are described in termsof software executing on various machines, the methods and systems mayalso be implemented as specifically-configured hardware, such asfield-programmable gate array (FPGA) specifically to execute the variousmethods. For example, examples can be implemented in digital electroniccircuitry, or in computer hardware, firmware, software, or in acombination thereof. In one example, a device may include a processor orprocessors. The processor comprises a computer-readable medium, such asa random access memory (RAM) coupled to the processor. The processorexecutes computer-executable program instructions stored in memory, suchas executing one or more computer programs. Such processors may comprisea microprocessor, a digital signal processor (DSP), anapplication-specific integrated circuit (ASIC), field programmable gatearrays (FPGAs), and state machines. Such processors may further compriseprogrammable electronic devices such as PLCs, programmable interruptcontrollers (PICs), programmable logic devices (PLDs), programmableread-only memories (PROMs), electronically programmable read-onlymemories (EPROMs or EEPROMs), or other similar devices.

Such processors may comprise, or may be in communication with, media,for example computer-readable storage media, that may store instructionsthat, when executed by the processor, can cause the processor to performthe steps described herein as carried out, or assisted, by a processor.Examples of computer-readable media may include, but are not limited to,an electronic, optical, magnetic, or other storage device capable ofproviding a processor, such as the processor in a web server, withcomputer-readable instructions. Other examples of media comprise, butare not limited to, a floppy disk, CD-ROM, magnetic disk, memory chip,ROM, RAM, ASIC, configured processor, all optical media, all magnetictape or other magnetic media, or any other medium from which a computerprocessor can read. The processor, and the processing, described may bein one or more structures, and may be dispersed through one or morestructures. The processor may comprise code for carrying out one or moreof the methods (or parts of methods) described herein.

The foregoing description of some examples has been presented only forthe purpose of illustration and description and is not intended to beexhaustive or to limit the disclosure to the precise forms disclosed.Numerous modifications and adaptations thereof will be apparent to thoseskilled in the art without departing from the spirit and scope of thedisclosure.

Reference herein to an example or implementation means that a particularfeature, structure, operation, or other characteristic described inconnection with the example may be included in at least oneimplementation of the disclosure. The disclosure is not restricted tothe particular examples or implementations described as such. Theappearance of the phrases “in one example,” “in an example,” “in oneimplementation,” or “in an implementation,” or variations of the same invarious places in the specification does not necessarily refer to thesame example or implementation. Any particular feature, structure,operation, or other characteristic described in this specification inrelation to one example or implementation may be combined with otherfeatures, structures, operations, or other characteristics described inrespect of any other example or implementation.

Use herein of the word “or” is intended to cover inclusive and exclusiveOR conditions. In other words, A or B or C includes any or all of thefollowing alternative combinations as appropriate for a particularusage: A alone; B alone; C alone; A and B only; A and C only; B and Conly; and A and B and C.

1. A sensing system comprising: an insect pathway to enable movement ofinsects from a first location to a second location; an insect detectorpositioned to detect insects traversing the insect pathway, the insectdetector comprising: a camera oriented and focused to capture imagesacross the insect pathway; and a processor in communication with anon-transitory computer-readable medium and configured to executeprocessor-executable code stored in the non-transitory computer-readablemedium to: obtain an image from the camera; identify at least onein-focus insect traversing the insect pathway in the image; and ignoreany out-of-focus insect in the image.
 2. The sensing system of claim 1,wherein the processor is configured to execute processor-executable codestored in the non-transitory computer-readable medium to detect thein-focus insect in the image using an edge detection technique.
 3. Thesensing system of claim 2, wherein the processor is configured toexecute processor-executable code stored in the non-transitorycomputer-readable medium to: generate an edge gradient map of the image,and detect the at least one in-focus insect in the image using the edgegradient map.
 4. The sensing system of claim 3, wherein the processorconfigured to execute processor-executable code stored in thenon-transitory computer-readable medium to: for each pixel in the image,determine an edge using pixels within a pixel window centered on therespective pixel, and generate the edge gradient map using thedetermined edges.
 5. The sensing system of claim 1, wherein theprocessor is configured to execute processor-executable code stored inthe non-transitory computer-readable medium to detect the insect in theimage using a machine learning technique.
 6. The sensing system of claim1, wherein the processor is configured to execute processor-executablecode stored in the non-transitory computer-readable medium to: identifythe in-focus insect in multiple consecutive images; and increment aninsect count by one for the identified in-focus insect in one image ofthe multiple consecutive images, and not increment the insect count forthe identified in-focus insect in the other images of the multipleconsecutive images.
 7. A method comprising: obtaining an image from acamera of a sensing system, the sensing system comprising an insectpathway to enable movement of insects from a first location to a secondlocation and an insect detector positioned to detect insects traversingthe insect pathway, the insect detector comprising the camera, thecamera oriented and focused to capture images across the insect pathway;identifying at least one in-focus insect traversing the insect pathwayin the image; and ignoring any out-of-focus insect in the image.
 8. Themethod of claim 7, further comprising detecting the in-focus insect inthe image using an edge detection technique
 9. The method of claim 8,further comprising: generating an edge gradient map of the image, anddetecting the at least one in-focus insect in the image using the edgegradient map.
 10. The method of claim 9, further comprising: for eachpixel in the image, determining an edge using pixels within a pixelwindow centered on the respective pixel, and generating the edgegradient map using the determined edges.
 11. The method of claim 7,further comprising detecting the in-focus insect in the image using amachine learning technique.
 12. The method of claim 7, furthercomprising: identifying the in-focus insect in multiple consecutiveimages; and incrementing an insect count by one for the identifiedin-focus insect in one image of the multiple consecutive images, and notincrementing the insect count for the identified in-focus insect in theother images of the multiple consecutive images.
 13. A non-transitorycomputer-readable medium comprising processor-executable instructionsconfigured to cause a processor to: obtain an image from a camera of asensing system, the sensing system comprising an insect pathway toenable movement of insects from a first location to a second locationand an insect detector positioned to detect insects traversing theinsect pathway, the insect detector comprising the camera, the cameraoriented and focused to capture images across the insect pathway;identify at least one in-focus insect traversing the insect pathway inthe image; and ignore any out-of-focus insect in the image.
 14. Thenon-transitory computer-readable medium of claim 13, further comprisingprocessor-executable instructions configured to cause a processor todetect the in-focus insect in the image using an edge detectiontechnique
 15. The non-transitory computer-readable medium of claim 14,further comprising processor-executable instructions configured to causea processor to: generate an edge gradient map of the image, and detectthe at least one in-focus insect in the image using the edge gradientmap.
 16. The non-transitory computer-readable medium of claim 15,further comprising further comprising processor-executable instructionsconfigured to cause a processor to: for each pixel in the image,determine an edge using pixels within a pixel window centered on therespective pixel, and generate the edge gradient map using thedetermined edges.
 17. The non-transitory computer-readable medium ofclaim 13, further comprising further comprising processor-executableinstructions configured to cause a processor to detect the in-focusinsect in the image using a machine learning technique.
 18. Thenon-transitory computer-readable medium of claim 13, further comprisingfurther comprising processor-executable instructions configured to causea processor to: identify the in-focus insect in multiple consecutiveimages; and increment an insect count by one for the identified in-focusinsect in one image of the multiple consecutive images, and notincrement the insect count for the identified in-focus insect in theother images of the multiple consecutive images.